xinan.lin a9adc9a9b6 [Linter] Add linter to detect device-bias hard code in test cases. (#152948) ...

Since XPU does not gate community pull requests, we’ve observed that contributors often hardcode "cuda" in functions decorated with @requires_gpu() when adding new test cases. This causes the tests to fail on XPU and breaks XPU CI.
This PR adds a linter to detect such issues automatically. An example is shown below.

```
  Error (TEST_DEVICE_BIAS) [device-bias]
    `@requires_gpu` function should not hardcode device='cuda'

        11670  |                .contiguous()
        11671  |            )
        11672  |
    >>> 11673  |        inp = torch.rand((64, 64), device="cuda") * 2 - 1
        11674  |        boundaries = torch.tensor([-0.9, -0.8, 0.1, 0.2, 0.5, 0.9])
        11675  |
        11676  |        self.common(fn, (inp, boundaries), check_lowp=False)

  Error (TEST_DEVICE_BIAS) [device-bias]
    `@requires_gpu` function should not hardcode .cuda() call

        11700  |            self.assertEqual(ref, res)
        11701  |
        11702  |            for offset2 in (0, 1, 2, 3, 4):
    >>> 11703  |                base2 = torch.randn(64 * 64 + 64, dtype=torch.float32).cuda()
        11704  |                inp2 = torch.as_strided(base2, (64, 64), (64, 1), offset2)
        11705  |                ref2 = fn(inp2)
        11706  |                res2 = fn_c(inp2)

  Error (TEST_DEVICE_BIAS) [device-bias]
    `@requires_gpu` function should not hardcode torch.device('cuda:0')

        11723  |            return x.sin() + x.cos()
        11724  |
        11725  |        base = torch.randn(
    >>> 11726  |            64 * 64 + 64, dtype=torch.float32, device=torch.device("cuda:0")
        11727  |        )
        11728  |
        11729  |        inp1 = torch.as_strided(base, (32, 32), (32, 1), 4)

  Error (TEST_DEVICE_BIAS) [device-bias]
    `@requires_gpu` function should not hardcode .to('cuda') call

        11771  |            torch.manual_seed(42)
        11772  |            base = torch.randn(64 * 64 + 64, dtype=torch.float32, device=self.device)
        11773  |            torch.manual_seed(42)
    >>> 11774  |            base_ref = torch.randn(64 * 64 + 64, dtype=torch.float32).to("cuda")
        11775  |
        11776  |            inp = torch.as_strided(base, size, stride, offset)
        11777  |            inp_ref = torch.as_strided(base_ref, size, stride, offset)
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/152948
Approved by: https://github.com/EikanWang, https://github.com/cyyever, https://github.com/malfet, https://github.com/jansel

2025-05-16 08:03:54 +00:00

..

adapters

[Linter] Add linter to detect device-bias hard code in test cases. (#152948)

2025-05-16 08:03:54 +00:00

clang_tidy

[BE][Easy] enable postponed annotations in tools (#129375)

2024-06-29 09:23:35 +00:00

__init__.py

First step to rearrange files in tools folder (#60473)

2021-06-24 10:13:58 -07:00